Experimental study of the impact of using a neural machine translation engine on the quality of translation of texts in the field of pharmacognosy

doi:10.26565/2227-8877-2020-92-15

Алла Сергіївна Ольховська Mykola Lukash Translation Studies Department of V. N. Karazin Kharkiv National University https://orcid.org/0000-0001-9034-4170
Олександр Олександрович Сіроклин Second-year Graduate Student at Mykola Lukash Translation Studies Department of V. N. Karazin Kharkiv National University

DOI: https://doi.org/10.26565/2227-8877-2020-92-15

Keywords: machine translation, neural machine translation system, future translators, translators’ training, professional translator competence, experimental research

Abstract

The article is devoted to the study of the impact of using the neural machine translation system Google Translate on the quality of translation of texts in the field of pharmacognosy. At the present stage, the work of a translator is impossible to imagine without the use of information and communication technologies, an important place among which is attributed to machine translation. It is considered that neural machine translation systems perform translation at a fairly high level, so that its use by a human translator can have a positive impact. That is why the aim of the study was to conduct an experiment to determine the impact of using a neural machine translation system on the quality of translation of texts in the field of pharmacognosy in terms of the number of errors and correctness of translating terminology. The article formulates a research hypothesis, describes the text chosen to conduct the study and the neural machine translation system, which was selected for this purpose, discloses the procedure for estimating the number of errors in translations and calculating the percentage of correctness of translating terminology, provides quantitative experimental data, and the results are illustrated in tables and drawings. The experimental study was conducted in the first semester of the 2020/2021 academic year (September) on the basis of an excerpt from a text in the field of pharmacognosy, which was translated by the neural machine translation system Google Translate and a translation student of the bachelor’s level. Both translations were checked in terms of quantity and quality (types) of errors, as well as in terms of correctness of translating domain-specific terminology. The results refuted our hypothesis, as the translation performed by the neural machine translation system Google Translate was worse, both in terms of the number of errors and the percentage of correctness of translating terminology as compared to the results demonstrated by the student.

Downloads

Download data is not yet available.

References

/

References

Bobkova I. A., Bur’yanova V. V. (2017). Farmakognoziya. [Pharmacognosy]. Kyiv : Medytsyna (in Ukrainian).

Bobkova I. A., Varlakhova L. V. (2018). Farmakognoziya. [Pharmacognosy]. Kyiv : Medytsyna (in Ukrainian).

Olkhovska A. S. (2017). Eksperymentalna perevirka efektyvnosti navchannia maibutnikh perekladachiv pysmovoho perekladu iz zastosuvanniam informatsiino-komunikatsiinykh tekhnolohii. [Experimental testing of the effectiveness of teaching translation to students with the use of information and communication technologies]. Visnyk KNLU. Seriia Pedahohika ta psykholohiia. Vypusk 27. P. 98–107 (in Ukrainian).

Khodakivska V. P., Bobkova I. A., Varlakhova L. V. (2018). Farmakohnoziia. [Pharmacognosy]. Kyiv : Medytsyna (in Ukrainian).

Chernovatyy L. M. (2013). Metodyka vykladannya perekladu. [Methods of teaching translation]. Vinnytsya : Nova Knyha (in Ukrainian).

Chernovatyi L. M. (2009). Problema otsiniuvannia pysmovykh robit maibutnikh perekladachiv. [The problem of assessing translations produced by future translators]. Visnyk Kharkivskoho natsionalnoho universytetu imeni V. N. Karazina. Seriia: Romano-hermanska filolohiia. Metodyka vykladannia inozemnykh mov. Vyp. 848. P. 257–262 (in Ukrainian).

Doherty S. (2016). The Impact of Translation Technologies on the Process and Product of Translation. International Journal of Communication. Vol. 10. P. 947–969.

Evans W. Ch. (2009). Trease and Evans Pharmacognosy. Edinburgh, New York : Saunders/Elsevier.

Toledo Báez M. C. (2018). Machine Translation and Postediting: Impact of Training and Directionality on Quality and Productivity. Revista Tradumàtica. Núm.16. Retrieved from: https://revistes.uab.cat/tradumatica/article/view/n16-toledo/177.

Vieira L. N., O’Hagan M., O’Sullivan C. (2020). Understanding the societal impacts of machine translation: a critical review of the literature on medical and legal use cases. Information, Communication & Society. Vol. 23. P. 1–18. https://doi.org/10.1080/1369118X.2020.1776370.

Бобкова І. А., Бур’янова В. В. Фармакогнозія. Київ : Медицина, 2017. 328 с.

Бобкова І. А., Варлахова Л. В. Фармакогнозія. Київ : Медицина, 2018. 504 с.

Ольховська А. С. Експериментальна перевірка ефективності навчання майбутніх перекладачів письмового перекладу із застосуванням інформаційно-комунікаційних технологій. Вісник КНЛУ. Серія Педагогіка та психологія. 2017. Випуск 27. С. 98–107.

Ходаківська В. П., Бобкова І. А., Варлахова Л. В. Фармакогнозія. Київ : Медицина, 2018. 192 с.

Черноватий Л. М. Методика викладання перекладу як спеціальності. Вінниця : Нова Книга, 2013. 376 с.

Черноватий Л. М. Проблема оцінювання письмових робіт майбутніх перекладачів. Вісник Харківського національного університету імені В. Н. Каразіна. Серія: Романо-германська філологія. Методика викладання іноземних мов. 2009. Вип. 848. С. 257–262.

Doherty S. The Impact of Translation Technologies on the Process and Product of Translation. International Journal of Communication. 2016. Vol. 10. P. 947–969.

Evans W. Ch. Trease and Evans Pharmacognosy. Edinburgh, New York : Saunders/Elsevier, 2009. 603 p.

Toledo Báez M. C. Machine Translation and Postediting: Impact of Training and Directionality on Quality and Productivity. Revista Tradumàtica. 2018. Núm.16. Retrieved from: file:///C:/Users/Asus-Notebook/Desktop/350188-Text%20de%20l'article-504739-1-10-20190207.pdf.

Vieira L. N., O’Hagan M., O’Sullivan C. Understanding the societal impacts of machine translation: a critical review of the literature on medical and legal use cases. Information, Communication & Society. 2020. Vol. 23. P. 1–18. https://doi.org/10.1080/1369118X.2020.1776370.